Perturbed Microbial Ecology in Myasthenia Gravis: Evidence from the Gut Microbiome and Fecal Metabolome

Explainable machine learning model for identifying key gut microbes and metabolites biomarkers associated with myasthenia gravis

Diagnostic markers for myasthenia gravis (MG) are limited; thus, innovative approaches are required for supportive diagnosis and personalized care. Gut microbes are associated with MG pathogenesis; however, few studies have adopted machine learning (ML) to identify the associations among MG, gut microbiota, and metabolites. In this study, we developed an explainable ML model to predict biomarkers for MG diagnosis. We enrolled 19 MG patients and 10 non-MG individuals. Stool samples were collected and microbiome assessment was performed using 16S rRNA sequencing. Untargeted metabolic profiling was conducted to identify fecal amplicon significant variants (ASVs) and metabolites. We developed an explainable ML model in which the top ASVs and metabolites are combined to identify the best predictive performance. This model uses the SHapley Additive exPlanations method to generate both global and personalized explanations. Fecal microbe-metabolite composition differed significantly between groups. The key bacterial families were Lachnospiraceae and Ruminococcaceae, and the top three features were Lachnospiraceae, inosine, and methylhistidine. An ML model trained with the top 1 % ASVs and top 15 % metabolites combined outperformed all other models. Personalized explanations revealed different patterns of microbe-metabolite contributions in patients with MG. The integration of the microbiota-metabolite features and the development of an explainable ML framework can accurately identify MG and provide personalized explanations, revealing the associations between gut microbiota, metabolites, and MG. An online calculator employing this algorithm was developed that provides a streamlined interface for MG diagnosis screening and conducting personalized evaluations.

Treatment response of venlafaxine induced alterations of gut microbiota and metabolites in a mouse model of depression

Antidepressants remain the first-line treatment for depression. However, the factors influencing medication response are still unclear. Accumulating evidence implicates an association between alterations in gut microbiota and antidepressant response. Therefore, the aim of this study is to investigate the role of the gut microbiota-brain axis in the treatment response of venlafaxine. After chronic social defeat stress and venlafaxine treatment, mice were divided into responders and non-responders groups. We compared the composition of gut microbiota using 16 S ribosomal RNA sequencing. Meanwhile, we quantified metabolomic alterations in serum and hippocampus, as well as hippocampal neurotransmitter levels using liquid chromatography-mass spectrometry. We found that the abundances of 29 amplicon sequence variants (ASVs) were significantly altered between the responders and non-responders groups. These ASVs belonged to 8 different families, particularly Muribaculaceae. Additionally, we identified 38 and 39 differential metabolites in serum and hippocampus between the responders and non-responders groups, respectively. Lipid, amino acid, and purine metabolisms were enriched in both serum and hippocampus. In hippocampus, the concentrations of tryptophan, phenylalanine, gamma-aminobutyric acid, glutamic acid, and glutamine were increased, while the level of succinic acid was decreased in the responders group, compared with the non-responders group. Our findings suggest that the gut microbiota may play a role in the antidepressant effect of venlafaxine by modulating metabolic processes in the central and peripheral tissues. This provides a novel microbial and metabolic framework for understanding the impact of the gut microbiota-brain axis on antidepressant response.

Dihydroartemisinin ameliorates experimental autoimmune myasthenia gravis by regulating CD4+ T cells and modulating gut microbiota

BACKGROUND

Dihydroartemisinin (DHA), a derivative and active metabolite of artemisinin, possesses various immunomodulatory properties. However, its role in myasthenia gravis (MG) has not been clearly explored. Here, we investigated the role of DHA in experimental autoimmune myasthenia gravis (EAMG) and its potential mechanisms.

METHODS

The AChR97-116 peptide-induced EAMG model was established in Lewis rats and treated with DHA. Flow cytometry was used to assess the release of Th cell subsets and Treg cells, and 16S rRNA gene amplicon sequence analysis was applied to explore the relationship between the changes in the intestinal flora after DHA treatment. In addition, network pharmacology and molecular docking were utilized to explore the potential mechanism of DHA against EAMG, which was further validated in the rat model by immunohistochemical and RT-qPCR for further validation.

RESULTS

In this study, we demonstrate that oral administration of DHA ameliorated clinical symptoms in rat models of EAMG, decreased the expression level of Th1 and Th17 cells, and increased the expression level of Treg cells. In addition, 16S rRNA gene amplicon sequence analysis showed that DHA restored gut microbiota dysbiosis in EAMG rats by decreasing Ruminococcus abundance and increasing the abundance of Clostridium, Bifidobacterium, and Allobaculum. Using network pharmacology, 103 potential targets of DHA related to MG were identified, and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis showed that PI3K-AKT signaling pathway was related to the treatment of DHA on EAMG. Meanwhile, molecular docking verified that DHA has good binding affinity to AKT1, CASP3, EGFR, and IGF1. Immunohistochemical staining showed that DHA treatment significantly inhibited the phosphorylated expression of AKT and PI3K in the spleen tissues of EAMG rats. In EAMG rats, RT-qPCR results also showed that DHA reduced the mRNA expression levels of PI3K and AKT1.

CONCLUSIONS

DHA ameliorated EAMG by inhibiting the PI3K-AKT signaling pathway, regulating CD4+ T cells and modulating gut microbiota, providing a novel therapeutic approach for the treatment of MG.

Fecal microbiota transplantation in autoimmune diseases - An extensive paper on a pathogenetic therapy

The role of infections in the pathogenesis of autoimmune diseases has long been recognized and reported. In addition to infectious agents, the internal composition of the "friendly" living bacteria, (microbiome) and its correlation to immune balance and dysregulation have drawn the attention of researchers for decades. Nevertheless, only recently, scientific papers regarding the potential role of transferring microbiome from healthy donor subjects to patients with autoimmune diseases has been proposed. Fecal microbiota transplantation or FMT, carries the logic of transferring microorganisms responsible for immune balance from healthy donors to individuals with immune dysregulation or more accurately for our paper, autoimmune diseases. Viewing the microbiome as a pathogenetic player allows us to consider FMT as a pathogenetic-based treatment. Promising results alongside improved outcomes have been demonstrated in patients with different autoimmune diseases following FMT. Therefore, in our current extensive review, we aimed to highlight the implication of FMT in various autoimmune diseases, such as inflammatory bowel disease, autoimmune thyroid and liver diseases, systemic lupus erythematosus, and type 1 diabetes mellitus, among others. Presenting all the aspects of FMT in more than 12 autoimmune diseases in one paper, to the best of our knowledge, is the first time presented in medical literature. Viewing FMT as such could contribute to better understanding and newer application of the model in the therapy of autoimmune diseases, indeed.

Omics approaches open new horizons in major depressive disorder: from biomarkers to precision medicine

Major depressive disorder (MDD) is a recurrent episodic mood disorder that represents the third leading cause of disability worldwide. In MDD, several factors can simultaneously contribute to its development, which complicates its diagnosis. According to practical guidelines, antidepressants are the first-line treatment for moderate to severe major depressive episodes. Traditional treatment strategies often follow a one-size-fits-all approach, resulting in suboptimal outcomes for many patients who fail to experience a response or recovery and develop the so-called "therapy-resistant depression". The high biological and clinical inter-variability within patients and the lack of robust biomarkers hinder the finding of specific therapeutic targets, contributing to the high treatment failure rates. In this frame, precision medicine, a paradigm that tailors medical interventions to individual characteristics, would help allocate the most adequate and effective treatment for each patient while minimizing its side effects. In particular, multi-omic studies may unveil the intricate interplays between genetic predispositions and exposure to environmental factors through the study of epigenomics, transcriptomics, proteomics, metabolomics, gut microbiomics, and immunomics. The integration of the flow of multi-omic information into molecular pathways may produce better outcomes than the current psychopharmacological approach, which targets singular molecular factors mainly related to the monoamine systems, disregarding the complex network of our organism. The concept of system biomedicine involves the integration and analysis of enormous datasets generated with different technologies, creating a "patient fingerprint", which defines the underlying biological mechanisms of every patient. This review, centered on precision medicine, explores the integration of multi-omic approaches as clinical tools for prediction in MDD at a single-patient level. It investigates how combining the existing technologies used for diagnostic, stratification, prognostic, and treatment-response biomarkers discovery with artificial intelligence can improve the assessment and treatment of MDD.

Gut microbiota-derived butyrate restores impaired regulatory T cells in patients with AChR myasthenia gravis via mTOR-mediated autophagy

More than 80% of patients with myasthenia gravis (MG) are positive for anti-acetylcholine receptor (AChR) antibodies. Regulatory T cells (Tregs) suppress overproduction of these antibodies, and patients with AChR antibody-positive MG (AChR MG) exhibit impaired Treg function and reduced Treg numbers. The gut microbiota and their metabolites play a crucial role in maintaining Treg differentiation and function. However, whether impaired Tregs correlate with gut microbiota activity in patients with AChR MG remains unknown. Here, we demonstrate that butyric acid-producing gut bacteria and serum butyric acid level are reduced in patients with AChR MG. Butyrate supplementation effectively enhanced Treg differentiation and their suppressive function of AChR MG. Mechanistically, butyrate activates autophagy of Treg cells by inhibiting the mammalian target of rapamycin. Activation of autophagy increased oxidative phosphorylation and surface expression of cytotoxic T-lymphocyte-associated protein 4 on Treg cells, thereby promoting Treg differentiation and their suppressive function in AChR MG. This observed effect of butyrate was blocked using chloroquine, an autophagy inhibitor, suggesting the vital role of butyrate-activated autophagy in Tregs of patients with AChR MG. We propose that gut bacteria derived butyrate has potential therapeutic efficacy against AChR MG by restoring impaired Tregs.

Dynamic changes in butyrate levels regulate satellite cell homeostasis by preventing spontaneous activation during aging

The gut microbiota plays a pivotal role in systemic metabolic processes and in particular functions, such as developing and preserving the skeletal muscle system. However, the interplay between gut microbiota/metabolites and the regulation of satellite cell (SC) homeostasis, particularly during aging, remains elusive. We propose that gut microbiota and its metabolites modulate SC physiology and homeostasis throughout skeletal muscle development, regeneration, and aging process. Our investigation reveals that microbial dysbiosis manipulated by either antibiotic treatment or fecal microbiota transplantation from aged to adult mice, leads to the activation of SCs or a significant reduction in the total number. Furthermore, employing multi-omics (e.g., RNA-seq, 16S rRNA gene sequencing, and metabolomics) and bioinformatic analysis, we demonstrate that the reduced butyrate levels, alongside the gut microbial dysbiosis, could be the primary factor contributing to the reduction in the number of SCs and subsequent impairments during skeletal muscle aging. Meanwhile, butyrate supplementation can mitigate the antibiotics-induced SC activation irrespective of gut microbiota, potentially by inhibiting the proliferation and differentiation of SCs/myoblasts. The butyrate effect is likely facilitated through the monocarboxylate transporter 1 (Mct1), a lactate transporter enriched on membranes of SCs and myoblasts. As a result, butyrate could serve as an alternative strategy to enhance SC homeostasis and function during skeletal muscle aging. Our findings shed light on the potential application of microbial metabolites in maintaining SC homeostasis and preventing skeletal muscle aging.

Curcumin protects mice with myasthenia gravis by regulating the gut microbiota, short-chain fatty acids, and the Th17/Treg balance

Curcumin is widely used as a traditional drug in Asia. Interestingly, curcumin and its metabolites have been demonstrated to influence the microbiota. However, the effect of curcumin on the gut microbiota in patients with myasthenia gravis (MG) remains unclear. This study aimed to investigate the effects of curcumin on the gut microbiota community, short-chain fatty acids (SCFAs) levels, intestinal permeability, and Th17/Treg balance in a Torpedo acetylcholine receptor (T-AChR)-induced MG mouse model. The results showed that curcumin significantly alleviated the clinical symptoms of MG mice induced by T-AChR. Curcumin modified the gut microbiota composition, increased microbial diversity, and, in particular, reduced endotoxin-producing Proteobacteria and Desulfovibrio levels in T-AChR-induced gut dysbiosis. Moreover, we found that curcumin significantly increased fecal butyrate levels in mice with T-AChR-induced gut dysbiosis. Butyrate levels increased in conjunction with the increase in butyrate-producing species such as Oscillospira, Akkermansia, and Allobaculum in the curcumin-treated group. In addition, curcumin repressed the increased levels of lipopolysaccharide (LPS), zonulin, and FD4 in plasma. It enhanced Occludin expression in the colons of MG mice induced with T-AChR, indicating dramatically alleviated gut permeability. Furthermore, curcumin treatment corrected T-AChR-induced imbalances in Th17/Treg cells. In summary, curcumin may protect mice against myasthenia gravis by modulating both the gut microbiota and SCFAs, improving gut permeability, and regulating the Th17/Treg balance. This study provides novel insights into curcumin's clinical value in MG therapy.

Causal relationship between gut microbiota and myasthenia gravis: a two-sample Mendelian randomization study

Background

Previous observational studies have provided cumulative data linking gut microbiota to myasthenia gravis (MG). However, the causal link between the two remains unexplored. Hence, the current study was performed to explore the causal link between them.

Methods

Mendelian randomization (MR) analysis was conducted using the summary statistics of 211 gut microbiota taxa and the largest genome-wide association studies (GWAS) for MG currently available. The inverse variance-weighted (IVW), MR-Egger, weighted median, and weighted mode methods were employed to ascertain the causal influence. Sensitivity studies utilizing several methodologies were then used to assess the robustness of the findings. Lastly, to evaluate reverse causality, a reverse MR analysis was performed.

Results

Seven suggestive causal associations between the gastrointestinal microbiota and MG were identified based on the outcomes of the MR analysis. Specifically, phylum Actinobacteria (OR: 0.602, 95% CI: 0.405-0.896, p = 0.012), class Gammaproteobacteria (OR: 0.587, 95% CI: 0.357-0.968, p = 0.037), and families Defluviitaleaceae (OR: 0.695, 95% CI: 0.485-0.996, p = 0.047), Family XIII (OR: 0.614, 95% CI: 0.412-0.916, p = 0.017), and Peptococcaceae (OR: 0.698, 95% CI: 0.505-0.964, p = 0.029) had suggestive protective effects on MG, while order Mollicutes RF9 (OR: 1.424, 95% CI: 1.015-1.998, p = 0.041) and genus Faecalibacterium (OR: 1.763, 95% CI: 1.220-2.547, p = 0.003) were suggestive risk factors for MG. The outcomes indicate that neither heterogeneity nor horizontal pleiotropy had any discernible impact. Nevertheless, this reverse analysis did not reveal any apparent effect of MG on the gut microbiota composition.

Conclusion

The MR investigation has substantiated the suggestive causal connection between gut microbiota and MG, which may provide helpful insights for innovative therapeutic and preventative approaches for MG. Further randomized controlled trials are needed to elucidate the gut microbiota's precise role and therapeutic potential in the pathogenesis of MG.

Mendelian randomization analyses of known and suspected risk factors and biomarkers for myasthenia gravis overall and by subtypes

BACKGROUND

Myasthenia gravis (MG) is an autoimmune disease that affects neuromuscular junction. The literature suggests the involvement of circulating cytokines (CK), gut microbiota (GM), and serum metabolites (SM) with MG. However, this research is limited to observational trials, and comprehensive causal relationship studies have not been conducted. Based on published datasets, this investigation employed Mendelian Randomization (MR) to analyze the known and suspected risk factors and biomarkers causal association of MG and its subtypes.

METHODS

This research used two-sample MR and linkage disequilibrium score (LDSC) regression of multiple datasets to aggregate datasets acquired from the genome-wide association studies (GWAS) to assess the association of MG with 41-CK, 221-GM, and 486-SM. For sensitivity analysis and to validate the robustness of the acquired data, six methods were utilized, including MR-Egger regression, inverse variance weighting (IVW), weighted median, and MR-PRESSO.

RESULTS

The MR method identified 20 factors significantly associated with MG, including 2 CKs, 6 GMs, and 9 SMs. Further analysis of the factors related to the two MG subtypes, early-onset MG (EOMG) and late-onset MG (LOMG), showed that EOMG had a high overlap with MG in the intestinal flora, while LOMG had a greater similarity in CKs and SMs. Furthermore, LDSC regression analysis indicated that Peptococcaceae, oxidized biliverdin, and Kynurenine had significant genetic correlations with general MG, whereas EOMG was highly correlated with Intestinibacter, while LOMG had significant genetic associations with Kynurenine and Glucose.

CONCLUSION

This research furnishes evidence for the potential causal associations of various risk factors with MG and indicates a heterogeneous relationship between CKs, GMs, and SMs with MG subtypes.

Evidence for genetic causal relationships between gut microbiome, metabolites, and myasthenia gravis: a bidirectional Mendelian randomization study

Background

Myasthenia gravis (MG) is an autoimmune disease observed to have connections with gut microbiome. We aimed to systematically assess the causal relationships between gut microbiome, gut microbiome-derived metabolites, and MG using Mendelian randomization (MR) approach.

Methods

Summary-level genetic datasets from large-scale genome-wide association studies regarding 196 gut microbial taxa from the MiBioGen consortium (n=18,340), 72 derived metabolites from the TwinsUK and KORA studies (n=7,824), and antiacetylcholine receptor (AChR) antibody-positive MG (case=1,873, control=36,370) were employed for MR causal estimates. The inverse-variance weighted (IVW) method was utilized as the main analysis with MR-Egger, maximum likelihood, simple mode, and weighted median as complements. The tests of Cochran's Q, MR-Egger intercept, Steiger, MR-PRESSO and leave-one-out were implemented for sensitivity analyses.

Results

The forward MR estimates of IVW revealed significant causal associations of the abundance of phylum Actinobacteria, class Gammaproteobacteria, family Defluviitaleac, family Family XIII, and family Peptococcaceae with a reduced risk of MG. Conversely, the abundance of phylum Lentisphaerae, order Mollicutes RF9, order Victivallales, and genus Faecalibacterium was causally associated with an increased risk of MG. The reversed MR analysis proved negative causal correlations between the MG and the abundance of family Peptostreptococcaceae, genus Romboutsia, and genus Subdoligranulum. Regarding the derived metabolites, the IVW estimates revealed that elevated levels of beta-hydroxyisovalerate and methionine were causally associated with a decreased risk of MG, while increased levels of choline and kynurenine were linked to an increased risk of MG. Furthermore, genetically predicted MG was associated with a decreased level of cholesterol. The results obtained from complementary MR methods were similar. These findings remained robust in all sensitivity analyses.

Conclusion

Our MR findings support the causal effects of specific gut microbiome taxa and derived metabolites on AChR antibody-positive MG, and vice versa, yielding novel insights into prevention and therapy targets of MG. Future studies may be warranted for validation and pursuing the precise mechanisms.

Causal relationship between gut microbiota and myasthenia gravis: a bidirectional mendelian randomization study

BACKGROUND

Observational studies have demonstrated an association between gut microbiota and myasthenia gravis; however, the causal relationship between the two still lacks clarity. Our goals are to ascertain the existence of a bidirectional causal relationship between gut microbiota composition and myasthenia gravis, and to investigate how gut microbiota plays a role in reducing the risk of myasthenia gravis.

METHODS

We acquired gut microbiota data at the phylum, class, order, family, and genus levels from the MiBioGen consortium (N = 18,340) and myasthenia gravis data from the FinnGen Research Project (426 cases and 373,848 controls). In the two-sample Mendelian randomization analysis, we assessed the causal relationship between the gut microbiota and myasthenia gravis. We also conducted bidirectional MR analysis to determine the direction of causality. The inverse variance weighted, mendelian randomization-Egger, weighted median, simple mode, and weighted mode were used to test the causal relationship between the gut microbiota and severe myasthenia gravis. We used MR-Egger intercept and Cochran's Q test to assess for pleiotropy and heterogeneity, respectively. Furthermore, we utilized the MR-PRESSO method to evaluate horizontal pleiotropy and detect outliers.

RESULTS

In the forward analysis, the inverse-variance weighted method revealed that there is a positive correlation between the genus Lachnoclostridium (OR = 2.431,95%CI 1.047-5.647, p = 0.039) and the risk of myasthenia gravis. Additionally, the family Clostridiaceae1 (OR = 0.424,95%CI 0.202-0.889, p = 0.023), family Defluviitaleaceae (OR = 0.537,95%CI  0.290-0.995, p = 0.048), family Enterobacteriaceae (OR = 0.341,95%CI  0.135-0.865, p = 0.023), and an unknown genus (OR = 0.407,95%CI  0.209-0.793, p = 0.008) all demonstrated negative correlation with the risk of developing myasthenia gravis. Futhermore, reversed Mendelian randomization analysis proved a negative correlation between the risk of myasthenia gravis and genus Barnesiella (OR = 0.945,95%CI  0.906-0.985, p = 0.008).

CONCLUSION

Our research yielded evidence of a causality connection in both directions between gut microbiota and myasthenia gravis. We identified specific types of microbes associated with myasthenia gravis, which offers a fresh window into the pathogenesis of this disease and the possibility of developing treatment strategies. Nonetheless, more studies, both basic and clinical, are necessary to elucidate the precise role and therapeutic potential of the gut microbiota in the pathogenesis of myasthenia gravis.

Machine learning strategy for identifying altered gut microbiomes for diagnostic screening in myasthenia gravis

Myasthenia gravis (MG) is a neuromuscular junction disease with a complex pathophysiology and clinical variation for which no clear biomarker has been discovered. We hypothesized that because changes in gut microbiome composition often occur in autoimmune diseases, the gut microbiome structures of patients with MG would differ from those without, and supervised machine learning (ML) analysis strategy could be trained using data from gut microbiota for diagnostic screening of MG. Genomic DNA from the stool samples of MG and those without were collected and established a sequencing library by constructing amplicon sequence variants (ASVs) and completing taxonomic classification of each representative DNA sequence. Four ML methods, namely least absolute shrinkage and selection operator, extreme gradient boosting (XGBoost), random forest, and classification and regression trees with nested leave-one-out cross-validation were trained using ASV taxon-based data and full ASV-based data to identify key ASVs in each data set. The results revealed XGBoost to have the best predicted performance. Overlapping key features extracted when XGBoost was trained using the full ASV-based and ASV taxon-based data were identified, and 31 high-importance ASVs (HIASVs) were obtained, assigned importance scores, and ranked. The most significant difference observed was in the abundance of bacteria in the Lachnospiraceae and Ruminococcaceae families. The 31 HIASVs were used to train the XGBoost algorithm to differentiate individuals with and without MG. The model had high diagnostic classification power and could accurately predict and identify patients with MG. In addition, the abundance of Lachnospiraceae was associated with limb weakness severity. In this study, we discovered that the composition of gut microbiomes differed between MG and non-MG subjects. In addition, the proposed XGBoost model trained using 31 HIASVs had the most favorable performance with respect to analyzing gut microbiomes. These HIASVs selected by the ML model may serve as biomarkers for clinical use and mechanistic study in the future. Our proposed ML model can identify several taxonomic markers and effectively discriminate patients with MG from those without with a high accuracy, the ML strategy can be applied as a benchmark to conduct noninvasive screening of MG.

Altered gut microbiota and metabolites in untreated myasthenia gravis patients

Objective

The homeostasis of the immune system is influenced by the gut microbiota. Previous studies have reported dysbiosis in the gut microbiota of myasthenia gravis (MG) patients. To investigate potential alterations in gut microbiota and metabolites in newly diagnosed and untreated MG patients, we conducted a case-control study.

Methods

Fecal samples were collected from 11 newly diagnosed and untreated MG patients as well as 11 age-and sex-matched healthy controls. These samples underwent analysis for gut microbiota using 16S ribosomal RNA (rRNA) gene sequencing, while fecal metabolome was analyzed using liquid chromatography-electrospray tandem mass spectrometry system (LC-ESI-MS/MS).

Results

The microbial community richness (observed species) and diversity (Shannon and Simpson indices) were significantly lower in the MG group compared to the control group. Microbiota composition analysis revealed significant differences between the MG and control groups at phylum, family, and genus levels. Linear discriminant analysis effect size (LEfSe) analysis showed a substantial decrease in abundance of the genus Faecalibacterium within the MG group. Fecal metabolome analysis identified three up-regulated metabolites involved in amino acid metabolism (taurine, creatinine, L-carnitine), one up-regulated metabolite involved in lipid metabolism (oleic acid), with correlation analysis indicating a positive association between Faecalibacterium abundance and creatinine levels.

Conclusion

Our findings suggest that dysbiosis already exists in newly diagnosed and untreated MG patients, implying that dysbiosis within the gut microbiota may be an initiating factor contributing to MG pathogenesis. Furthermore, F. prausnitzii may hold promise as a probiotic for treating MG.

Gut microbiota in muscular atrophy development, progression, and treatment: New therapeutic targets and opportunities

Skeletal muscle atrophy is a debilitating condition that significantly affects quality of life and often lacks effective treatment options. Muscle atrophy can have various causes, including myogenic, neurogenic, and other factors. Recent investigation has underscored a compelling link between the gut microbiota and skeletal muscle. Discerning the potential differences in the gut microbiota associated with muscle atrophy-related diseases, understanding their influence on disease development, and recognizing their potential as intervention targets are of paramount importance. This review aims to provide a comprehensive overview of the role of the gut microbiota in muscle atrophy-related diseases. We summarize clinical and pre-clinical studies that investigate the potential for gut microbiota modulation to enhance muscle performance and promote disease recovery. Furthermore, we delve into the intricate interplay between the gut microbiota and muscle atrophy-related diseases, drawing from an array of studies. Emerging evidence suggests significant differences in gut microbiota composition in individuals with muscle atrophy-related diseases compared with healthy individuals. It is conceivable that these alterations in the microbiota contribute to the pathogenesis of these disorders through bacterium-related metabolites or inflammatory signals. Additionally, interventions targeting the gut microbiota have demonstrated promising results for mitigating disease progression in animal models, underscoring the therapeutic potential of modulating the gut microbiota in these conditions. By analyzing the available literature, this review sheds light on the involvement of the gut microbiota in muscle atrophy-related diseases. The findings contribute to our understanding of the underlying mechanisms and open avenues for development of novel therapeutic strategies targeting the gut-muscle axis.

Astragaloside IV ameliorates experimental autoimmune myasthenia gravis by regulating CD4 + T cells and altering gut microbiota

BACKGROUND

Myasthenia gravis (MG) is an antibody-mediated autoimmune disease and its pathogenesis is closely related to CD4 + T cells. In recent years, gut microbiota is considered to play an important role in the pathogenesis of MG. Astragaloside IV (AS-IV) is one of the main active components extracted from Astragalus membranaceus and has immunomodulatory effects. To study the immunomodulatory effect of AS-IV and the changes of gut microbiota on experimental autoimmune myasthenia gravis (EAMG) mice, we explore the possible mechanism of AS-IV in improving MG.

METHODS

In this study, network pharmacology was utilized to screen the crucial targets of AS-IV in the treatment of MG. Subsequently, a Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis was performed to identify potential pathways through which AS-IV acts against MG. Furthermore, experimental investigations were conducted to validate the underlying mechanism of AS-IV in MG treatment. Before modeling, 5 mice were randomly selected as the control group (CFA group), and the other 10 were induced to EAMG model. These mice were randomly divided into EAMG group and EAMG + AS-IV group, n = 5/group. In EAMG + AS-IV group, AS-IV was administered by gavage. CFA and EAMG groups were given the same volume of PBS. Body weight, grip strength and clinical symptoms were assessed and recorded weekly. At the last administration, the feces were collected for 16S RNA microbiota analysis. The levels of Treg, Th1 and Th17 cells in spleen and Th1 and Th17 cells in thymus were detected by flow cytometry. The levels of IFN-γ, IL-17 and TGF-β in serum were measured by ELISA. Furthermore, fecal microbial transplantation (FMT) experiments were performed for exploring the influence of changed intestinal flora on EAMG. After EAMG model was induced, the mice were treated with antibiotics daily for 4 weeks to germ-free. Then germ-free EAMG mice were randomly divided into two groups: FMT EAMG group, FMT AS-IV group, n = 3/group. Fecal extractions from EAMG and EAMG + AS-IV groups as gathered above were used to administered daily to the respective groups for 4 weeks. Body weight, grip strength and clinical symptoms were assessed and recorded weekly. The levels of Treg, Th1 and Th17 cells in spleen and Th1 and Th17 cells in thymus were detected at the last administration. The levels of IFN-γ, IL-17 and TGF-β in serum were measured by ELISA.

RESULTS

The network pharmacology and KEGG pathway analysis revealed that AS-IV regulates T cell pathways, including T cell receptor signaling pathway and Th17 cell differentiation, suggesting its potential in improving MG. Further experimental verification demonstrated that AS-IV administration improved muscle strength and body weight, reduced the level of Th1 and Th17 cells, enhanced the level of Treg cells, and resulted in alterations of the gut microbiota, including changes in beta diversity, the Firmicutes/Bacteroidetes (F/B) ratio, and the abundance of Clostridia in EAMG mice. We further conducted FMT tests and demonstrated that the EAMG Abx-treated mice which were transplanted the feces of mice treated with AS-IV significantly alleviated myasthenia symptoms, reduced Th1 and Th17 cells levels, and increased Treg cell levels.

CONCLUSION

This study speculated that AS-IV ameliorates EAMG by regulating CD4 + T cells and altering the structure and species of gut microbiota of EAMG.

Gut microbiota: a new insight into neurological diseases

ABSTRACT

In the last decade, it has become increasingly recognized that a balanced gut microbiota plays an important role in maintaining the health of the host. Numerous clinical and preclinical studies have shown that changes in gut microbiota composition are associated with a variety of neurological diseases, e.g., Parkinson's disease, Alzheimer's disease, and myasthenia gravis. However, the underlying molecular mechanisms are complex and remain unclear. Behavioral phenotypes can be transmitted from humans to animals through gut microbiota transplantation, indicating that the gut microbiota may be an important regulator of neurological diseases. However, further research is required to determine whether animal-based findings can be extended to humans and to elucidate the relevant potential mechanisms by which the gut microbiota regulates neurological diseases. Such investigations may aid in the development of new microbiota-based strategies for diagnosis and treatment and improve the clinical management of neurological disorders. In this review, we describe the dysbiosis of gut microbiota and the corresponding mechanisms in common neurological diseases, and discuss the potential roles that the intestinal microbiome may play in the diagnosis and treatment of neurological disorders.

Impact of Gut Microbiota on the Peripheral Nervous System in Physiological, Regenerative and Pathological Conditions

It has been widely demonstrated that the gut microbiota is responsible for essential functions in human health and that its perturbation is implicated in the development and progression of a growing list of diseases. The number of studies evaluating how the gut microbiota interacts with and influences other organs and systems in the body and vice versa is constantly increasing and several 'gut-organ axes' have already been defined. Recently, the view on the link between the gut microbiota (GM) and the peripheral nervous system (PNS) has become broader by exceeding the fact that the PNS can serve as a systemic carrier of GM-derived metabolites and products to other organs. The PNS as the communication network between the central nervous system and the periphery of the body and internal organs can rather be affected itself by GM perturbation. In this review, we summarize the current knowledge about the impact of gut microbiota on the PNS, with regard to its somatic and autonomic divisions, in physiological, regenerative and pathological conditions.

Microbiota dysbiosis and myasthenia gravis: Do all roads lead to Rome?

Dysregulated immune system with a failure to recognize self from non-self-antigens is one of the common pathogeneses seen in autoimmune diseases. The complex interplay of genetic and environmental factors is important for the occurrence and development of the disease. Among the environmental factors, disturbed gut microbiota (gut dysbiosis) has recently attracted particular attention, especially with advancement in human microbiome research. Although the alterations in microbiota have been seen in various autoimmune diseases, including those of nervous system, there is paucity of information on neuromuscular system diseases. Myasthenia gravis (MG) is one such rare autoimmune disease of neuromuscular junction, and is caused by generation of pathogenic autoantibodies to components of the postsynaptic muscle endplate. In the recent years, accumulating evidences have endorsed the key role of host microbiota, particularly those of gut, in the pathogenesis of MG. Differential microbiota composition, characterized by increased abundance of Fusobacteria, Bacteroidetes, and Proteobacteria, and decreased abundance of Actinobacteria and Firmicutes, has been seen in MG patients in comparison to healthy subjects. Disturbance of microbiota composition, particularly reduced ratio of Firmicutes/Bacteroidetes, alter the gut permeability, subsequently triggering the immunological response. Resultant reduction in levels of short chain fatty acids (SCFAs) is another factor contributing to the immunological response in MG patients. Modulation of gut microbiota via intervention of probiotics, prebiotics, synbiotics, postbiotics (metabiotics), and fecal microbiota transplantation (FMT) is considered to be the futuristic approach for the management of MG. This review summarizes the role of gut microbiota and their metabolites (postbiotics) in the progression of MG. Also, various bacteriotherapeutic approaches involving gut microbiota are discussed for the prevention of MG progression.

The Role of Human Microbiota in Myasthenia Gravis: A Narrative Review

Myasthenia gravis (MG) is an autoimmune neuromuscular disease characterized by fluctuating weakness of the skeletal muscles. Although antibodies against the neuromuscular junction components are recognized, the MG pathogenesis remains unclear, even if with a well-known multifactorial character. However, the perturbations of human microbiota have been recently suggested to contribute to MG pathogenesis and clinical course. Accordingly, some products derived from commensal flora have been demonstrated to have anti-inflammatory effects, while other have been shown to possess pro-inflammatory properties. In addition, patients with MG when compared with age-matched controls showed a distinctive composition in the oral and gut microbiota, with a typical increase in Streptococcus and Bacteroides and a reduction in Clostridia as well as short-chain fatty acid reduction. Moreover, restoring the gut microbiota perturbation has been evidenced after the administration of probiotics followed by an improvement of symptoms in MG cases. To highlight the role of the oral and gut microbiota in MG pathogenesis and clinical course, here, the current evidence has been summarized and reviewed.

Traditional Chinese medicine improves myasthenia gravis by regulating the symbiotic homeostasis of the intestinal microbiota and host

Myasthenia gravis (MG) is an autoimmune disease caused by autoantibodies that is dependent on T-cell immunity and complement participation and mainly involves neuromuscular junctions. In this study, 30 patients with myasthenia gravis were selected and divided into pretreatment (Case group) and posttreatment (Treatment group) and 30 healthy volunteers (CON group) were included. Among them, the treatment group was treated with Modified Buzhong Yiqi Decoction (MBZYQD), and the levels of antibodies such as AChR, Musk and Titin in blood and intestinal microbiota were compared before treatment (Case group), after treatment (Treatment group) and in healthy volunteers (CON group). The results showed that after treatment with MBZYQD, the antibody levels of AChR, MuSK, and Titin and the inflammatory factor level of IL-6, IL-1β, and IL-22 in MG patients decreased significantly and nearly returned to a healthy level. In addition, after treatment with MBZYQD, the diversity, structure and function of intestinal microorganisms in MG patients also recovered to a healthy level. At the phylum level, the relative abundance of Proteobacteria in the Case group increased significantly, accompanied by a significant decrease in the relative abundance of Bacteroides compared with that in the CON group, the relative abundance of Proteobacteria and Bacteroides in the Treatment group was similar to that in the CON group. At the genus level, the relative abundance of Shigella in the Case group was significantly increased, accompanied by a significant decrease in the relative abundance of Prevotella, and the relative abundance of Shigella and Prevotella in Treatment group was similar to that in the CON group. Moreover, the fluorobenzoate degradation pathway (KO00364) was significantly increased in the Case group, while this pathway was significantly decreased in the Treatment group. In conclusion, MBZYQD can improve the immune function of the host by regulating the diversity, structure and function of the intestinal microbiota to treat myasthenia gravis.

Perturbed gut microbiota is gender-segregated in unipolar and bipolar depression

OBJECTIVE

This study aimed to explore the gender specificity of gut microbiome in patients with unipolar and bipolar depression disorder by analyzing the data of gut microbiome in this two mental disorders and healthy people.

METHODS

A case-control study using 16S ribosomal RNA gene sequencing from fecal samples of MDD (male set, n = 43; female set, n = 77) and BD (male set, n = 82; female set, n = 83) compared with HCs (male set, n = 71; female set, n = 100) was conducted. Linear discriminant analysis was used to identify microbial characteristics. Through cooccurrence analysis, the potential correlations of the differential gut microbiota in different genders was explored. Finally, the gender-specific distinguishing microorganisms were identified as biomaker, and the diagnostic performance was verified by five-fold cross validation.

RESULTS

A specific cluster was found enriched only in female MDD set, including 4 Bacteroideae OTUs. Similarly, 3 Lachnospiraceae OTUs was found significantly increased in female BD compared with other groups. In addition, the consistent enrichment of Pseudomonadacea in male and female may be the characteristic disease-related gut microbiota of BD. Besides, the diagnostic potential of gender specific biomarker panel in male (male validation AUC: 0.758-0.874, accurancy: 0.693-0.792; female validation AUC: 0.727-0.883, accurancy: 0.678-0.781) and female (male validation AUC: 0.787-0.883, accurancy: 0.719-0.784; female validation AUC: 0.795-0.898, accurancy: 0.689-0.838) has also been identified and confirmed.

CONCLUSIONS

The microbiological changes in both MDD and BD are sex specific, and gender specific biomarker panel has better diagnostic performance, which provide a certain reference in sex difference for future clinical differentiation and microbial intervention.

Oral Microbiota Profile in a Group of Anti-AChR Antibody–Positive Myasthenia Gravis Patients

Myasthenia gravis (MG) is an autoimmune disorder caused by autoantibodies directed against the postsynaptic membrane at the neuromuscular junction. Perturbation of gut microbiota is thought to contribute to the development of MG, as reflected by fecal metabolomic signatures in humans, but there have been few studies on the relationship between oral microbiota profile and MG. The current study evaluated the correlation between oral microbiota composition and diversity and anti-acetylcholinereceptor (AChR) antibody–positive MG by comparing oral microbiota communities of patients (n = 20) and healthy controls (HCs; n = 20) by 16S rRNA gene sequencing. Principal coordinate analysis and Adonis analysis revealed significant differences in oral microflora profile between the twogroups. Compared to HCs, the abundance of the phyla Firmicutes and Actinobacteria and genera Streptococcus, Rothia, and Lachnoanerobaculum was significantly increased whereas that of phyla Proteobacteria and Spirochaetotaand genera Neisseria, Haemophilus, and Treponema was significantly decreased in MG patients. The Kyoto Encyclopedia of Genes and Genomes pathway analysis showed that the biosynthesis of ansamycins and amino acid metabolism pathways were altered in MG. These results indicate that oral microbiota composition is perturbed in patients with anti-AChR antibody–positive MG, providing new potential avenues for targeted therapeutic interventions.

Altered Metabolism of the Microbiota-Gut-Brain Axis Is Linked With Comorbid Anxiety in Fecal Recipient Mice of Myasthenia Gravis

Myasthenia gravis (MG) comorbid anxiety seriously affects the progress of MG. However, the exact relationship remains poorly understood. Recently, our preliminary study has revealed that intestinal microbe disturbance is closely related to MG. Therefore, further exploration of whether the microbiome is involved in MG comorbid anxiety is warranted. In this study, gas chromatography-mass spectrometry metabolomics analysis was used to characterize the metabotype of feces, serum, and three brain regions involved in emotion (i.e., the prefrontal cortex, hippocampus, and striatum), which were obtained from mice that were colonized with fecal microbiota from patients with MG (MMb), healthy individuals (HMb), or co-colonization of both patients and healthy individuals (CMb). Functional enrichment analysis was used to explore the correlation between the “microbiota–gut–brain” (MGB) axis and anxiety-like behavior. The behavioral test showed that female MMb exhibited anxiety-like behavior, which could be reversed by co-colonization. Moreover, metabolic characterization analysis of the MGB axis showed that the metabotype of gut-brain communication was significantly different between MMb and HMb, and 146 differential metabolites were jointly identified. Among these, 44 metabolites in feces; 12 metabolites in serum; 7 metabolites in hippocampus; 2 metabolites in prefrontal cortex; and 6 metabolites in striatum were reversed by co-colonization. Furthermore, the reversed gut microbiota mainly belonged to bacteroides and firmicutes, which were highly correlated with the reversed metabolites within the MGB axis. Among three emotional brain regions, hippocampus was more affected. Therefore, disturbances in gut microbiota may be involved in the progress of anxiety-like behavior in MG due to the MGB axis.

Integrated Fecal Microbiome and Metabolomics Reveals a Novel Potential Biomarker for Predicting Tibial Dyschondroplasia in Chickens

Tibial dyschondroplasia (TD) is a metabolic tibial-tarsal disorder occurring in fast-growing poultry, and its diagnosis is mainly based on an invasive method. Here, we profiled the fecal gut microbiome and metabolome of broilers with and without TD to identify potential non-invasive and non-stress biomarkers of TD. First, TD broilers with the most pronounced clinical signs during the experiment were screened and faecal samples were collected for integrated microbiome and metabolomics analysis. Moreover, the diagnostic potential of identified biomarkers was further validated throughout the experiment. It was noted that the microbial and metabolic signatures of TD broilers differed from those of normal broilers. TD broilers were characterized by enriched bacterial OTUs of the genus Klebsiella, and depleted genera [Ruminococcus], Dorea, Ruminococcus, Oscillospira, Ochrobactrum, and Sediminibacterium. In addition, a total of 189 fecal differential metabolites were identified, mainly enriched in the purine, vitamin and amino acid metabolism, which were closely associated with differential microbiota and tibia-related indicators. Furthermore, three fecal metabolites were screened, including 4-hydroxybenzaldehyde, which distinguished TD from normal broilers with extremely high specificity and was superior to serum bone markers. These results indicated that gut microbiota equilibrium might influence the pathogenesis of TD by modulating host metabolism, and the identified fecal metabolite 4-hydroxybenzaldehyde might be a potential and non-invasive biomarker for predicting TD in chickens.

Effectiveness of modified Buzhong Yiqi decoction in treating myasthenia gravis: study protocol for a series of N-of-1 trials

Background

Myasthenia gravis (MG) is an acquired autoimmune disease with high heterogeneity. The disease is chronic, relapsing repeatedly and progressive with acute exacerbation occasionally. Although the treatment of MG has developed, it is still unsatisfactory and has some unexpected side effects. Traditional Chinese medicine (TCM) has shown great potential in MG treatment, including relief of muscle weakness syndrome, improvement of patient’s quality of life, and reduction of side effects of western medicine. The purpose of this study is to evaluate the effectiveness of modified Buzhong Yiqi decoction (MBYD) as an add-on therapy for MG through a small series of N-of-1 trials.

Methods

Single-centre, randomized, double-blind, 3 crossover N-of-1 trials will be conducted to enroll patients with MG diagnosed as spleen-stomach deficiency syndrome or spleen-kidney deficiency syndrome in TCM. Each N-of-1 trial has 3 cycles of two 4-week periods containing the MBYD period and placebo period. The wash-out interval of 1 week is prior to switching each period. Primary outcome: quantitative myasthenia gravis (QMG). Secondary outcomes: the following scales: myasthenia gravis composite (MGC), myasthenia gravis activities of daily living profile (MG-ADL), myasthenia gravis quality of life (MG-QOL); the level of CD4+FoxP3+Treg cells and cytokines (IL-4, IL-17A, INF-γ, TGF-β) in the peripheral blood; the alterations of the composition of gut microbiota; reduction of the side effects of western medicine.

Discussion

Used by WinBUGS software, we will conduct a hierarchical Bayesian statistical method to analyze the efficacy of MBYD in treating MG in individuals and populations. Some confounding variables such as TCM syndrome type and potential carryover effect of TCM will be introduced into the hierarchical Bayesian statistical method to improve the sensitivity and applicability of the trials, and the use of prior available information within the analysis may improve the sensitivity of the results of a series of N-of-1 trials, from both the individual and population level to study the efficacy of TCM syndrome differentiation. We assumed that this study would reveal that MBYD is effective for MG and provide robust evidence of the efficacy of TCM to treat MG.

Trial registration

Chinese Clinical Trial Register, ID: ChiCTR2000040477, registration on 29 November 2020.

Exploring the Gut Microbiome in Myasthenia Gravis

The human gut microbiota is vital for maintaining human health in terms of immune system homeostasis. Perturbations in the composition and function of microbiota have been associated with several autoimmune disorders, including myasthenia gravis (MG), a neuromuscular condition associated with varying weakness and rapid fatigue of the skeletal muscles triggered by the host’s antibodies against the acetylcholine receptor (AChR) in the postsynaptic muscle membrane at the neuromuscular junction (NMJ). It is hypothesized that perturbation of the gut microbiota is associated with the pathogenesis of MG. The gut microbiota community profiles are usually generated using 16S rRNA gene sequencing. Compared to healthy individuals, MG participants had an altered gut microbiota’s relative abundance of bacterial taxa, particularly with a drop in Clostridium. The microbial diversity related to MG severity and the overall fecal short-chain fatty acids (SCFAs) were lower in MG subjects. Changes were also found in terms of serum biomarkers and fecal metabolites. A link was found between the bacterial Operational Taxonomic Unit (OTU), some metabolite biomarkers, and MG’s clinical symptoms. There were also variations in microbial and metabolic markers, which, in combination, could be used as an MG diagnostic tool, and interventions via fecal microbiota transplant (FMT) could affect MG development. Probiotics may influence MG by restoring the gut microbiome imbalance, aiding the prevention of MG, and lowering the risk of gut inflammation by normalizing serum biomarkers. Hence, this review will discuss how alterations of gut microbiome composition and function relate to MG and the benefits of gut modulation.

Effect of Fufang Huangqi Decoction on the Gut Microbiota in Patients With Class I or II Myasthenia Gravis

Objective

To investigate the effect of Fufang Huangqi Decoction on the gut microbiota in patients with class I or II myasthenia gravis (MG) and to explore the correlation between gut microbiota and MG (registration number, ChiCTR2100048367; registration website, http://www.chictr.org.cn/listbycreater.aspx; NCBI: SRP338707).

Methods

In this study, microbial community composition and diversity analyses were carried out on fecal specimens from MG patients who did not take Fufang Huangqi Decoction (control group, n = 8) and those who took Fufang Huangqi Decoction and achieved remarkable alleviation of symptoms (medication group, n = 8). The abundance, diversity within and between habitats, taxonomic differences and corresponding discrimination markers of gut microbiota in the control group and medicated group were assessed.

Results

Compared with the control group, the medicated group showed a significantly decreased abundance of Bacteroidetes (P < 0.05) and significantly increased abundance of Actinobacteria at the phylum level, a significantly decreased abundance of Bacteroidaceae (P < 0.05) and significantly increased abundance of Bifidobacteriaceae at the family level and a significantly decreased abundance of Blautia and Bacteroides (P < 0.05) and significantly increased abundance of Bifidobacterium, Lactobacillus and Roseburia at the genus level. Compared to the control group, the medicated group had decreased abundance, diversity, and genetic diversity of the communities and increased coverage, but the differences were not significant (P > 0.05); the markers that differed significantly between communities at the genus level and influenced the differences between groups were Blautia, Bacteroides, Bifidobacterium and Lactobacillus.

Conclusions

MG patients have obvious gut microbiota-associated metabolic disorders. Fufang Huangqi Decoction regulates the gut microbiota in patients with class I or II MG by reducing the abundance of Blautia and Bacteroides and increasing the abundance of Bifidobacterium and Lactobacillus. The correlation between gut microbiota and MG may be related to cell-mediated immunity.

Imaging the in vivo growth patterns of bacteria in human gut Microbiota

How to study the unculturable bacteria in the laboratory is one of the major challenges in human gut microbiota research. The resulting lack of microbiology knowledge of this "dark matter" greatly hinders further understanding of our gut microbiota. Here, to characterize the in vivo growth and division of human gut bacteria, we report the integrative use of STAMP (sequential tagging with D-amino acid-based metabolic probes) and fluorescence in situ hybridization (FISH) in a human microbiota-associated mouse model. After stable colonization of the human fecal microbiotas in germ-free mice, two fluorescent D-amino acid probes were sequentially administered by gavage, and the dually labeled peptidoglycan of the bacteria provided a chronological recording of their cell wall syntheses. Following taxonomic identification with FISH staining, the growth patterns of 32 species, including 5 currently unculturables, were identified. Surprisingly, we found that many bacterial species in the human microbiota were significantly shorter than those in the mouse gut microbiota. An imaging database for gut bacteria ̶ Microbiome Atlas was built for summarizing STAMP imaging of bacteria from different microbiotas, which can be contributed by the microbiota research community worldwide. This integrative imaging strategy and the database will promote our understanding of the bacterial cytology in gut microbiotas and facilitate communications among cellular microbiologists.

Gut Microbiota as Regulators of Th17/Treg Balance in Patients With Myasthenia Gravis

Myasthenia gravis (MG) is an acquired neurological autoimmune disorder characterized by dysfunctional transmission at the neuromuscular junction, with its etiology associated with genetic and environmental factors. Anti-inflammatory regulatory T cells (Tregs) and pro-inflammatory T helper 17 (Th17) cells functionally antagonize each other, and the immune imbalance between them contributes to the pathogenesis of MG. Among the numerous factors influencing the balance of Th17/Treg cells, the gut microbiota have received attention from scholars. Gut microbial dysbiosis and altered microbial metabolites have been seen in patients with MG. Therefore, correcting Th17/Treg imbalances may be a novel therapeutic approach to MG by modifying the gut microbiota. In this review, we initially review the association between Treg/Th17 and the occurrence of MG and subsequently focus on recent findings on alterations of gut microbiota and microbial metabolites in patients with MG. We also explore the effects of gut microbiota on Th17/Treg balance in patients with MG, which may provide a new direction for the prevention and treatment of this disease.

A pilot exploration of multi-omics research of gut microbiome in major depressive disorders

The pathophysiology of major depressive disorder (MDD) remains obscure. Recently, the microbiota-gut-brain (MGB) axis's role in MDD has an increasing attention. However, the specific mechanism of the multi-level effects of gut microbiota on host metabolism, immunity, and brain structure is unclear. Multi-omics approaches based on the analysis of different body fluids and tissues using a variety of analytical platforms have the potential to provide a deeper understanding of MGB axis disorders. Therefore, the data of metagenomics, metabolomic, inflammatory factors, and MRI scanning are collected from the two groups including 24 drug-naïve MDD patients and 26 healthy controls (HCs). Then, the correlation analysis is performed in all omics. The results confirmed that there are many markedly altered differences, such as elevated Actinobacteria abundance, plasma IL-1β concentration, lipid, vitamin, and carbohydrate metabolism disorder, and diminished grey matter volume (GMV) of inferior frontal gyrus (IFG) in the MDD patients. Notably, three kinds of discriminative bacteria, Ruminococcus bromii, Lactococcus chungangensis, and Streptococcus gallolyticus have an extensive correlation with metabolome, immunology, GMV, and clinical symptoms. All three microbiota are closely related to IL-1β and lipids (as an example, phosphoethanolamine (PEA)). Besides, Lactococcus chungangensis is negatively related to the GMV of left IFG. Overall, this study demonstrate that the effects of gut microbiome exert in MDD is multifactorial.

Colonization of fecal microbiota from patients with neonatal necrotizing enterocolitis exacerbates intestinal injury in germfree mice subjected to necrotizing enterocolitis-induction protocol via alterations in butyrate and regulatory T cells

BACKGROUND

Necrotizing enterocolitis (NEC) remains a life-threatening disease in neonates. Numerous studies have shown a correlation between the intestinal microbiota and NEC, but the causal link remains unclear. This study aimed to demonstrate the causal role of gut microbiota in NEC and explore potential mechanisms involved.

METHODS

Eighty-one fecal samples from patients with NEC and eighty-one matched controls (matched to the NEC infants by gestational age, birth weight, date of birth, mode of delivery and feeding patterns) were collected. To explore if altered gut microbiota contributes to the pathogenesis of NEC, fecal microbiota transplantation (FMT) was carried out in germ-free (GF) mice prior to a NEC-induction protocol that included exposure to hypoxia and cold stress. Butyric acid was also administered to demonstrate its role in NEC. The fecal microbiota from patients and mice were analyzed by 16S rRNA gene sequencing analysis. Short chain fatty acid (SCFA) levels were measured by gas chromatography-mass spectrometry (GC-MS). The ontogeny of T cells and regulatory T cells (T_regs) in lamina propria mononuclear cells (LPMC) from the ileum of patients and mice were isolated and analyzed by flow cytometry.The transcription of inflammatory cytokines was quantified by qRT-PCR.

RESULTS

NEC patients had increased Proteobacteria and decreased Firmicutes and Bacteroidetes compared to fecal control samples, and the level of butyric acid in the NEC group was lower than the control group. FMT in GF mice with samples from NEC patients achieved a higher histological injury scores when compared to mice that received FMT with control samples. Alterations in microbiota and butyrate levels were maintained in mice following FMT. The ratio of T_reg/CD4⁺T (T_helper) cells was reduced in both NEC patients and mice modeling NEC following FMT.

CONCLUSIONS

The microbiota was found to have NEC and the microbial butyrate-T_reg axis was identified as a potential mechanism for the observed effects.

Inhibition of Rho Kinase by Fasudil Ameliorates Cognition Impairment in APP/PS1 Transgenic Mice via Modulation of Gut Microbiota and Metabolites

Background: Fasudil, a Rho kinase inhibitor, exerts therapeutic effects in a mouse model of Alzheimer's disease (AD), a chronic neurodegenerative disease with progressive loss of memory. However, the mechanisms remain unclear. In addition, the gut microbiota and its metabolites have been implicated in AD.

Methods: We examined the effect of fasudil on learning and memory using the Morris water-maze (MWM) test in APPswe/PSEN1dE9 transgenic (APP/PS1) mice (8 months old) treated (i.p.) with fasudil (25 mg/kg/day; ADF) or saline (ADNS) and in age- and gender-matched wild-type (WT) mice. Fecal metagenomics and metabolites were performed to identify novel biomarkers of AD and elucidate the mechanisms of fasudil induced beneficial effects in AD mice.

Results: The MWM test showed significant improvement of spatial memory in APP/PS1 mice treated with fasudil as compared to ADNS. The metagenomic analysis revealed the abundance of the dominant phyla in all the three groups, including Bacteroidetes (23.7–44%) and Firmicutes (6.4–26.6%), and the increased relative abundance ratio of Firmicutes/Bacteroidetes in ADNS (59.1%) compared to WT (31.7%). In contrast, the Firmicutes/Bacteroidetes ratio was decreased to the WT level in ADF (32.8%). Lefse analysis of metagenomics identified s_Prevotella_sp_CAG873 as an ADF potential biomarker, while s_Helicobacter_typhlonius and s_Helicobacter_sp_MIT_03-1616 as ADNS potential biomarkers. Metabolite analysis revealed the increment of various metabolites, including glutamate, hypoxanthine, thymine, hexanoyl-CoA, and leukotriene, which were relative to ADNS or ADF microbiota potential biomarkers and mainly involved in the metabolism of nucleotide, lipids and sugars, and the inflammatory pathway.

Conclusions: Memory deficit in APP/PS1 mice was correlated with the gut microbiome and metabolite status. Fasudil reversed the abnormal gut microbiota and subsequently regulated the related metabolisms to normal in the AD mice. It is believed that fasudil can be a novel strategy for the treatment of AD via remodeling of the gut microbiota and metabolites. The novel results also provide valuable references for the use of gut microbiota and metabolites as diagnostic biomarkers and/or therapeutic targets in clinical studies of AD.

The Influence of Cesarean Section on the Composition and Development of Gut Microbiota During the First 3 Months of Life

The intestinal microbiota has emerged as a critical regulator of growth and development in the early postnatal period of life. Cesarean section (CS) delivery is one of the strongest disrupting factors of the normal colonization process and has been reported as a risk factor for disorders in later life. In this study, we dynamically and longitudinally evaluated the impact of CS on the initial colonization pattern and development of gut microbiota by 16 healthy Chinese infants with fecal samples collected at 9 time points (day 5, day 8, day 11, week 2, week 4, week 6, week 7, month 2, and month 3) during the first 3 months of life. The V3–V4 regions of 16S rRNA gene were analyzed by Illumina sequencing. In comparison with vaginally delivered (VD) infants, infants born by CS showed decreased relative abundance of Bacteroides and Parabacteroides and enrichment of Clostridium_sensu_stricto_1, Enterococcus, Klebsiella, Clostridioides, and Veillonella. Most interestingly, Firmicutes/Bacteroidetes ratio was found to be significantly higher in the CS group than in the VD group from day 5 until month 3. Besides, the results of microbial functions showed that the VD group harbored significantly higher levels of functional genes in vitamin B6 metabolism at day 5, day 8, week 2, week 4, week 6, week 7, month 2, and month 3 and taurine and hypotaurine metabolism at day 5, while the phosphotransferase system and starch and sucrose metabolism involved functional genes were plentiful in the CS group at day 11, week 2, week 4, week 6, week 7, and month 2 and at week 2, week 7, and month 2, respectively. Our results establish a new evidence that CS affected the composition and development of gut microbiota in the first 3 months and provide a novel insight into strategies for CS-related disorders in later life.

Calprotectin as potential novel biomarker in myasthenia gravis

Myasthenia gravis (MG) is the most common autoimmune disease affecting the neuromuscular junction by specific autoantibodies. The etiology of MG and its heterogeneity in clinical courses are poorly understood, although it was recently shown that gut microbial dysbiosis plays a critical role. Since levels of Calprotectin (CLP) seem to correlate with level of dysbiosis, we hypothesize that CLP may serve as potential disease activity biomarker in MG. Sera from 251 patients with MG and 90 controls were analyzed in an explorative, cross-sectional design. Prospectively, we tested CLP levels in MG patients up to 3 years. Association of CLP levels with socio-demographics, disease activity (quantitative myasthenia gravis (QMG) score, myasthenia gravis-specific Activities of Daily Living scale (MG-ADL)), antibody (Abs) status, history of myasthenic crisis, treatment regime, and history of thymectomy were investigated using univariate analysis. Mean baseline serum levels of CLP were significantly higher in MG patients compared to controls (4.3 μg/ml vs. 2.1 μg/ml; p < 0.0001). Higher levels of CLP were associated with a higher clinical disease severity measured by MGFA classification and QMG score. Nevertheless, the only weak correlation of CLP with clinical outcome parameters needs confirmation in future studies. Currently, there are no validated blood biomarkers for MG. The significantly elevated CLP and mild correlation with parameters of disease activity suggests that CLP holds promise as a biomarker for measurement of individual disease severity.

Disturbed microbial ecology in Alzheimer's disease: evidence from the gut microbiota and fecal metabolome

BACKGROUND

Gut microbiota (GMB) alteration has been reported to influence the Alzheimer's disease (AD) pathogenesis through immune, endocrine, and metabolic pathways. This study aims to investigate metabolic output of the dysbiosis of GMB in AD pathogenesis. In this study, the fecal microbiota and metabolome from 21 AD participants and 44 cognitively normal control participants were measured. Untargeted GMB taxa was analyzed through 16S ribosomal RNA gene profiling based on next-generation sequencing and fecal metabolites were quantified by using ultrahigh performance liquid chromatography-mass spectrometry (UPLC-MS).

RESULTS

Our analysis revealed that AD was characterized by 15 altered gut bacterial genera, of which 46.7% (7/15 general) was significantly associated with a series of metabolite markers. The predicted metabolic profile of altered gut microbial composition included steroid hormone biosynthesis, N-Acyl amino acid metabolism and piperidine metabolism. Moreover, a combination of 2 gut bacterial genera (Faecalibacterium and Pseudomonas) and 4 metabolites (N-Docosahexaenoyl GABA, 19-Oxoandrost-4-ene-3,17-dione, Trigofoenoside F and 22-Angeloylbarringtogenol C) was able to discriminate AD from NC with AUC of 0.955 in these 65 subjects.

CONCLUSIONS

These findings demonstrate that gut microbial alterations and related metabolic output changes may be associated with pathogenesis of AD, and suggest that fecal markers might be used as a non-invasive examination to assist screening and diagnosis of AD.

Gut bacterial microbiota in patients with myasthenia gravis: results from the MYBIOM study

Background:

Myasthenia gravis (MG) is an autoimmune neuromuscular disease, with gut microbiota considered to be a pathogenetic factor. Previous pilot studies have found differences in the gut microbiota of patients with MG and healthy individuals. To determine whether gut microbiota has a pathogenetic role in MG, we compared the gut microbiota of patients with MG with that of patients with non-inflammatory and inflammatory neurological disorders of the peripheral nervous system (primary endpoint) and healthy volunteers (secondary endpoint).

Methods:

Faecal samples were collected from patients with MG (n = 41), non-inflammatory neurological disorder (NIND, n = 18), chronic inflammatory demyelinating polyradiculoneuropathy (CIDP, n = 6) and healthy volunteers (n = 12). DNA was isolated from these samples, and the variable regions of the 16S rRNA gene were sequenced and statistically analysed.

Results:

No differences were found in alpha- and beta-diversity indices computed between the MG, NIND and CIDP groups, indicating an unaltered bacterial diversity and structure of the microbial community. However, the alpha-diversity indices, namely Shannon, Chao 1 and abundance-based coverage estimators, were significantly reduced between the MG group and healthy volunteers. Deltaproteobacteria and Faecalibacterium were abundant within the faecal microbiota of patients with MG compared with controls with non-inflammatory diseases.

Conclusion:

Although the overall diversity and structure of the gut microbiota did not differ between the MG, NIND and CIDP groups, the significant difference in the abundance of Deltaproteobacteria and Faecalibacterium supports the possible role of gut microbiota as a contributor to pathogenesis of MG. Further studies are needed to confirm these findings and to develop possible treatment strategies.

Metagenome-wide association study of gut microbiome revealed potential microbial marker set for diagnosis of pediatric myasthenia gravis

BACKGROUND

Myasthenia gravis (MG) is an acquired immune-mediated disorder of the neuromuscular junction that causes fluctuating skeletal muscle weakness and fatigue. Pediatric MG and adult MG have many different characteristics, and current MG diagnostic methods for children are not quite fit. Previous studies indicate that alterations in the gut microbiota may be associated with adult MG. However, it has not been determined whether the gut microbiota are altered in pediatric MG patients.

METHODS

Our study recruited 53 pediatric MG patients and 46 age- and gender-matched healthy controls (HC). We sequenced the fecal samples of recruited individuals using whole-genome shotgun sequencing and analyzed the data with in-house bioinformatics pipeline.

RESULTS

We built an MG disease classifier based on the abundance of five species, Fusobacterium mortiferum, Prevotella stercorea, Prevotella copri, Megamonas funiformis, and Megamonas hypermegale. The classifier obtained 94% area under the curve (AUC) in cross-validation and 84% AUC in the independent validation cohort. Gut microbiome analysis revealed the presence of human adenovirus F/D in 10 MG patients. Significantly different pathways and gene families between MG patients and HC belonged to P. copri, Clostridium bartlettii, and Bacteroides massiliensis. Based on functional annotation, we found that the gut microbiome affects the production of short-chain fatty acids (SCFAs), and we confirmed the decrease in SCFA levels in pediatric MG patients via serum tests.

CONCLUSIONS

The study indicated that altered fecal microbiota might play vital roles in pediatric MG's pathogenesis by reducing SCFAs. The microbial markers might serve as novel diagnostic methods for pediatric MG.

The Association of Post-Stroke Cognitive Impairment and Gut Microbiota and its Corresponding Metabolites

BACKGROUND

Post-stroke cognitive impairment (PSCI) is an important factor causing disabilities after acute ischemic stroke (AIS). Emerging evidence suggested that gut microbiota play an important role in cognitive impairment.

OBJECTIVE

This study aimed to explore the association between PSCI and gut microbiota.

METHOD

65 patients with newly diagnostic AIS finished the fecal collection on admission and cognitive assessment 3 months later in the clinic. Fecal samples were subjected to 16SrRNA gene sequencing and gas chromatography-mass spectrometry analysis. Additionally, we enrolled new 18 AIS patients, whose treatment was supplemented by probiotics, to assess the potential of microbial treatment in PSCI.

RESULTS

PSCI patients were characterized by the significantly decreased alpha-diversity, disturbed microbial composition, and corresponding metabolites compared with non-PSCI patients. Increased Fusobacterium and deficiency of microbial metabolized short-chain fatty acids (SCFAs) were significantly associated with PSCI. A model based on gut microbiota and SCFAs could predict 3 months or longer PSCI early and accurately after stroke onset. While traditional probiotic administration had little effect on PSCI, it could ameliorate patients' mood, including depression and anxiety in the 3 months after stroke.

CONCLUSION

Our study revealed the association between PSCI and gut microbiota and its corresponding metabolites for the first time, suggesting the potential for applying microbiota and its corresponding metabolites to early clinical diagnosis and treatment of PSCI.

Alteration of Gut Microbiome and Correlated Lipid Metabolism in Post-Stroke Depression

Background

The pathogenesis of post-stroke depression (PSD) remains largely unknown. There is growing evidence indicating that gut microbiota participates in the development of brain diseases through the gut-brain axis. Here, we aim to determine whether and how microbial composition and function altered among control, stroke and PSD rats.

Materials and Methods

After the PSD rat model was successfully established, gut microbiome combined with fecal metabolome approach were performed to identify potentially PSD-related gut microbes and their functional metabolites. Then, correlations between behavior indices and altered gut microbes, as well as correlations between altered gut microbial operational taxonomic units (OTUs) with differential metabolites in PSD rats were explored. Enrichment analysis was also conducted to uncover the crucial metabolic pathways related to PSD.

Results

Although there were some alterations in the microbiome and metabolism of the control and stroke rats, we found that the microbial and metabolic phenotypes of PSD rats were significantly different. The microbial composition of PSD showed a decreased species richness indices, characterized by 22 depleted OTUs mainly belonging to phylum Firmicutes, genus Blautia and Streptococcus. In addition, PSD was associated with disturbances of fecal metabolomics, among them Glutamate, Maleic acid, 5-Methyluridine, Gallocatechin, 1,5-Anhydroglucitol, L-Kynurenine, Daidzein, Cyanoalanine, Acetyl Alanine and 5-Methoxytryptamine were significantly related to disturbed gut microbiome (P ≤ 0.01). Disordered fecal metabolomics in PSD rats mainly assigned to lipid, amino acid, carbohydrate and nucleotide metabolism. The steroid biosynthesis was particularly enriched in PSD.

Conclusions

Our findings suggest that gut microbiome may participate in the development of PSD, the mechanism may be related to the regulation of lipid metabolism.

Jianpi Jieyu Decoction, An Empirical Herbal Formula, Exerts Psychotropic Effects in Association With Modulation of Gut Microbial Diversity and GABA Activity

Background: Recent studies suggest that gut microbiota was associated with the bidirectional gut-brain axis which could modulate neuropsychological functions of the central nervous system. Gut microbiota could produce gamma aminobutyric acid (GABA) that could modulate the gut-brain axis response. Jianpi Jieyu (JPJY) decoction, a traditional Chinese formula, is mainly composed of Astragalus membranaxeus and Radix Pseudostellariae. Although the JPJY decoction has been used to treat the depression in China, the potential action of its antidepressant has not been well understood. Thus this study was aim to investigate the role of JPJY improve gut microbiota homeostasis in the chronic stress induced depressive mice. Methods: The antidepressant effect of JPJY on chronic unpredictable mild stress (CUMS) mice was evaluated by using sucrose preference test, tail suspension test and forced swim test. Fatigue-like behaviors were evaluated using degree of redness, grip strength test, and exhaustive swimming test. The new object recognition test was used to evaluate cognition performance. Fecal samples were collected and taxonomical analysis of intestinal microbial distribution was conducted with 16S rDNA. Serum level of GABA was measured using high performance liquid chromatography (HPLC). The expression of GluR1 and p-Tau protein in the hippocampus was determined using Western blotting. Results: The dose of 9.2 g/kg JPJY produced antidepressant-like effects. JPJY and its major components also modulated gut microbiota diversity in the CUMS mice. Serum level of GABA and the expressions of hippocampal GluR1 and p-Tau were reversed after the administration of JPJY in CUMS mice. Conclusion: JPJY regulates gut microbiota to produce antidepressant-like effect and improve cognition deficit in depressive mice while its molecular mechanism possibly be enhanced NR1 and Tau expression in hippocampus and increased GABA in serum.

The gut microbiome modulates gut-brain axis glycerophospholipid metabolism in a region-specific manner in a nonhuman primate model of depression

Emerging research demonstrates that microbiota-gut-brain (MGB) axis changes are associated with depression onset, but the mechanisms underlying this observation remain largely unknown. The gut microbiome of nonhuman primates is highly similar to that of humans, and some subordinate monkeys naturally display depressive-like behaviors, making them an ideal model for studying these phenomena. Here, we characterized microbial composition and function, and gut-brain metabolic signatures, in female cynomolgus macaque (Macaca fascicularis) displaying naturally occurring depressive-like behaviors. We found that both microbial and metabolic signatures of depressive-like macaques were significantly different from those of controls. The depressive-like monkeys had characteristic disturbances of the phylum Firmicutes. In addition, the depressive-like macaques were characterized by changes in three microbial and four metabolic weighted gene correlation network analysis (WGCNA) clusters of the MGB axis, which were consistently enriched in fatty acyl, sphingolipid, and glycerophospholipid metabolism. These microbial and metabolic modules were significantly correlated with various depressive-like behaviors, thus reinforcing MGB axis perturbations as potential mediators of depression onset. These differential brain metabolites were mainly mapped into the hippocampal glycerophospholipid metabolism in a region-specific manner. Together, these findings provide new microbial and metabolic frameworks for understanding the MGB axis' role in depression, and suggesting that the gut microbiome may participate in the onset of depressive-like behaviors by modulating peripheral and central glycerophospholipid metabolism.

The Association of Gut Microbiota and Treg Dysfunction in Autoimmune Diseases

Autoimmune conditions affect 23 million Americans or 7% of the US population. There are more than 100 autoimmune disorders, affecting every major organ system in humans. This chapter aims to further explain Treg dysfunction autoimmune disorders, including monogenic primary immune deficiency such as immune dysregulation polyendocrinopathy, enteropathy, X-linked inheritance (IPEX) syndrome, and polygenic autoimmune diseases with Treg dysfunction such as multiple sclerosis (MS), inflammatory bowel disease (IBD), and food allergy. These conditions are associated with an abnormal small intestinal and colonic microbiome. Some disorders clearly improve with therapies aimed at microbial modification, including probiotics and fecal microbiota transplantation (FMT). Approaches to prevent and treat these disorders will need to focus on the acquisition and maintenance of a healthy colonic microbiota, in addition to more focused approaches at immune suppression during acute disease exacerbations.

Modulation of immune responses by bile acid receptor agonists in myasthenia gravis

Bile acids bind to multiple receptors, including Takeda G protein-coupled receptor 5 (TGR5) and farnesoid-X-receptors alpha (FXRα). We compared the response of PBMCs to the activation of these receptors in healthy controls and myasthenic patients. We found that TGR5 is a more potent negative regulator of T cell cytokine response than FXRα in both groups. In contrast, TGR5 and FXRα agonists elicit distinct B cell responses in myasthenia compared to controls, specifically on the frequency of IL-6⁺ B cells and regulatory B cells, as well as IL-10 secretion from PBMCs. We propose that TGR5 is a potential therapeutic target in myasthenia.

Landscapes of bacterial and metabolic signatures and their interaction in major depressive disorders

Gut microbiome disturbances have been implicated in major depressive disorder (MDD). However, little is known about how the gut virome, microbiome, and fecal metabolome change, and how they interact in MDD. Here, using whole-genome shotgun metagenomic and untargeted metabolomic methods, we identified 3 bacteriophages, 47 bacterial species, and 50 fecal metabolites showing notable differences in abundance between MDD patients and healthy controls (HCs). Patients with MDD were mainly characterized by increased abundance of the genus Bacteroides and decreased abundance of the genera Blautia and Eubacterium These multilevel omics alterations generated a characteristic MDD coexpression network. Disturbed microbial genes and fecal metabolites were consistently mapped to amino acid (γ-aminobutyrate, phenylalanine, and tryptophan) metabolism. Furthermore, we identified a combinatorial marker panel that robustly discriminated MDD from HC individuals in both the discovery and validation sets. Our findings provide a deep insight into understanding of the roles of disturbed gut ecosystem in MDD.

Altered gut bacterial and metabolic signatures and their interaction in gestational diabetes mellitus

Emerging evidence indicates that the gut microbiome can modulate metabolic homeostasis, and thus may influence the development of gestational diabetes mellitus (GDM). However, whether and how the gut microbiome and its correlated metabolites change in GDM is uncertain. Herein we compare the gut microbial compositions, and fecal and urine metabolomes, of 59 patients with GDM versus 48 pregnant healthy controls (HCs). We showed that the microbial and metabolic signatures of GDM patients were significantly different from those of HCs. Compared to HCs, the GDM subjects were characterized by enriched bacterial operational taxonomic units (OTUs) of the family Lachnospiraceae, and depleted OTUs of the families Enterobacteriaceae and Ruminococcaceae. Some altered gut microbes were significantly correlated with glucose values and fetal ultrasonography indexes. Moreover, we identified four fecal and 15 urine metabolites that discriminate GDM from HC. These differential metabolites are mainly involved in carbohydrate and amino acid metabolism. Significantly, co-occurrence network analysis revealed that Lachnospiraceae and Enterobacteriaceae bacterial OTUs formed strong co-occurring relationships with metabolites involved in carbohydrate and amino acid metabolism, suggesting that disturbed gut microbiome may mediate GDM. Furthermore, we identified a novel combinatorial marker panel that could distinguish GDM from HC subjects with high accuracy. Together our findings demonstrate that altered microbial composition and metabolic function may be relevant to the pathogenesis and pathophysiology of GDM.

Differential Gut Microbiota and Fecal Metabolites Related With the Clinical Subtypes of Myasthenia Gravis

Myasthenia gravis (MG) is a devastating acquired autoimmune disease. Previous studies have observed that disturbances of gut microbiome may attribute to the development of MG through fecal metabolomic signatures in humans. However, whether there were differential gut microbial and fecal metabolomic phenotypes in different subtypes of MG remains unclear. Here, our objective was to explore whether the microbial and metabolic signatures of ocular (OMG) and generalized myasthenia gravis (GMG) were different, and further identify the shared and distinct markers for patients with OMG and GMG. In this study, 16S ribosomal RNA (rRNA) gene sequencing and gas chromatography-mass spectrometry (GC/MS) were performed to capture the microbial and metabolic signatures of OMG and GMG, respectively. Random forest (RF) classifiers was used to identify the discriminative markers for OMG and GMG. Compared with healthy control (HC) group, GMG group, but not OMG group, showed a significant decrease in α-phylogenetic diversity. Both OMG and GMG groups, however, displayed significant gut microbial and metabolic disorders. Totally, we identified 20 OTUs and 9 metabolites specific to OMG group, and 23 OTUs and 7 metabolites specific to GMG group. Moreover, combinatorial biomarkers containing 15 discriminative OTUs and 2 differential metabolites were capable of discriminating OMG and GMG from each other, as well as from HCs, with AUC values ranging from 0.934 to 0.990. In conclusion, different subtypes of MG harbored differential gut microbiota, which generated discriminative fecal metabolism.

Gut microbial clues to bipolar disorder: State-of-the-art review of current findings and future directions

Trillions of microorganisms inhabiting in the human gut play an essential role in maintaining physical and mental health. The connections between gut microbiome and neuropsychiatric diseases have been recently identified. The pathogenesis of bipolar disorder, a spectrum of diseases manifesting with mood and energy fluctuations, also seems to be involved in the bidirectional modulation of the microbiome-gut-brain (MGB) axis. In this review, we briefly introduce the concept of MGB axis, and then focus on the previous findings in human studies associated with bipolar disorder. These studies provided preliminary evidences on the gut microbial alterations in bipolar disorder. Limitations in these studies and future directions in this research field, such as fecal microbiome transplantation and microbiome-targeted therapy, were discussed. A research framework linking gut microbiome to determinants and health-related outcomes in BD was also proposed. Better characterizing and understanding of gut microbial biosignatures in bipolar patients contribute to clarify the etiology of this intractable disease and pave the new way for treatment innovation.

Patient-specific multi-omics models and the application in personalized combination therapy

The rapid advancement of high-throughput technologies and sharp decrease in cost have opened up the possibility to generate large amount of multi-omics data on an individual basis. The development of high-throughput -omics, including genomics, epigenomics, transcriptomics, proteomics, metabolomics and microbiomics, enables the application of multi-omics technologies in the clinical settings. Combination therapy, defined as disease treatment with two or more drugs to achieve efficacy with lower doses or lower drug toxicity, is the basis for the care of diseases like cancer. Patient-specific multi-omics data integration can help the identification and development of combination therapies. In this review, we provide an overview of different -omics platforms, and discuss the methods for multi-omics, high-throughput, data integration, personalized combination therapy.

Gut Microbial Signatures Can Discriminate Unipolar from Bipolar Depression

Discriminating depressive episodes of bipolar disorder (BD) from major depressive disorder (MDD) is a major clinical challenge. Recently, gut microbiome alterations are implicated in these two mood disorders; however, little is known about the shared and distinct microbial characteristics in MDD versus BD. Here, using 16S ribosomal RNA (rRNA) gene sequencing, the microbial compositions of 165 subjects with MDD are compared with 217 BD, and 217 healthy controls (HCs). It is found that the microbial compositions are different between the three groups. Compared to HCs, MDD is characterized by altered covarying operational taxonomic units (OTUs) assigned to the Bacteroidaceae family, and BD shows disturbed covarying OTUs belonging to Lachnospiraceae, Prevotellaceae, and Ruminococcaceae families. Furthermore, a signature of 26 OTUs is identified that can distinguish patients with MDD from those with BD or HCs, with area under the curve (AUC) values ranging from 0.961 to 0.986 in discovery sets, and 0.702 to 0.741 in validation sets. Moreover, 4 of 26 microbial markers correlate with disease severity in MDD or BD. Together, distinct gut microbial compositions are identified in MDD compared to BD and HCs, and a novel marker panel is provided for distinguishing MDD from BD based on gut microbiome signatures.